ESSEC METALAB

RESEARCH

A KERNEL SEARCH HEURISTIC FOR THE MULTI-VEHICLE INVENTORY ROUTING PROBLEM

[ARTICLE] This paper studies an inventory routing problem aiming to minimize total distribution costs by using a matheuristic approach that leverages tabu search and mixed-integer linear programming.

by Claudia Archetti (ESSEC Business School), Gianfranco Guastaroba, Diana L. Huerta-Muñoz, M. Grazia Speranza

In this paper an inventory routing problem is studied in which the goal is to determine an optimal distribution plan to replenish a set of customers by routing a limited fleet of capacitated vehicles over a discrete planning horizon. Each customer consumes a per period quantity of product and has a maximum inventory capacity. The goal is to minimize the total distribution cost that comprises the routing and the inventory holding costs. A matheuristic is presented, which uses the information gathered by a tabu search to build a sequence of mixed‐integer linear programming problems of small size. Extensive computational experiments are conducted on a large set of benchmark instances. The results show that the matheuristic outperforms other state‐of‐the‐art algorithms in terms of average solution quality.

[Please read the research paper here]

Research list
arrow-right
Résumé de la politique de confidentialité

Ce site utilise des cookies afin que nous puissions vous fournir la meilleure expérience utilisateur possible. Les informations sur les cookies sont stockées dans votre navigateur et remplissent des fonctions telles que vous reconnaître lorsque vous revenez sur notre site Web et aider notre équipe à comprendre les sections du site que vous trouvez les plus intéressantes et utiles.